Observational Study
Copyright ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. May 26, 2020; 8(10): 1923-1931
Published online May 26, 2020. doi: 10.12998/wjcc.v8.i10.1923
Four-microRNA signature for detection of type 2 diabetes
Li-Na Yan, Xin Zhang, Fang Xu, Yuan-Yuan Fan, Biao Ge, Hui Guo, Zi-Ling Li
Li-Na Yan, Fang Xu, Yuan-Yuan Fan, Biao Ge, Hui Guo, Zi-Ling Li, Department of Endocrinology, Inner Mongolia Baogang Hospital, Baotou 014010, Inner Mongolia Autonomous Region, China
Xin Zhang, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Interventional Therapy Department, Peking University Cancer Hospital and Institute, Beijing 100142, China
Author contributions: Yan LN and Zhang X designed the study; Yan LN, Xu F, Fan YY, Ge B, and Guo H performed the research; Yan LN, Zhang X, and Li ZL analyzed the data; Yan LN wrote the paper and Li ZL revised the manuscript for final submission; Yan LN and Zhang X contributed equally to this study.
Supported by the National Key R& D Program of China, No. 2016YFC0106604.
Institutional review board statement: The study was reviewed and approved by the Ethics Committee of the Third Hospital Affiliated to Inner Mongolia Medical University (Inner Mongolia Baogang Hospital).
Informed consent statement: All study participants or their legal guardian provided written informed consent prior to study enrollment.
Conflict-of-interest statement: We declare that we have no financial or personal relationships with other individuals or organizations that can inappropriately influence our work and that there is no professional or other personal interest of any nature in any product, service and/or company that could be construed as influencing the position presented in or the review of the manuscript.
Data sharing statement: No additional data are available.
STROBE statement: The authors have read the STROBE Statement – checklist of items, and the manuscript was prepared and revised according to the STROBE Statement – checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Zi-Ling Li, MD, Director, Department of Endocrinology, Inner Mongolia Baogang Hospital, No. 20, Shaoxian Road, Kundulun District, Baotou 014010, Inner Mongolia Autonomous Region, China. 3301922766@qq.com
Received: February 24, 2020
Peer-review started: February 24, 2020
First decision: March 24, 2020
Revised: April 2, 2020
Accepted: April 15, 2020
Article in press: April 15, 2020
Published online: May 26, 2020
Processing time: 91 Days and 5.2 Hours
Abstract
BACKGROUND

Sensitive, novel, and accurate biomarkers for the detection of physiological changes in type 2 diabetes (T2DM) at an early stage are urgently needed.

AIM

To build a multi-parameter diagnostic model for the early detection of T2DM.

METHODS

MiR-148b, miR-223, miR-130a, and miR-19a levels were detected by real-time polymerase chain reaction in serum of healthy controls, individuals with impaired glucose regulation, and T2DM patients. The diagnostic value of miR-148b, miR-223, miR-130a, and miR-19a, alone or in combination, was analyzed.

RESULTS

The area under the curve (AUC) of miR-223, which had the best diagnostic value for discriminating the impaired glucose regulation and T2DM groups, was 0.84, and the sensitivity and specificity were 73.37% and 81.37%, respectively. The AUC of the four-miRNA signature was 0.90, and the sensitivity and specificity were 78.82% and 88.23%, respectively. In the validation set, the AUC was 0.88, and the sensitivity and specificity were 78.36% and 87.63%, respectively.

CONCLUSION

In summary, we have built a multi-parameter diagnostic model consisting of miR-148b, miR-223, miR-130a, and miR-19a for the detection of T2DM. It may be a potential tool for the early detection of T2DM.

Keywords: Type 2 diabetes, Serum, MicroRNAs, Multi-parameter, Biomarker

Core tip: The expression of microRNAs in serum is stable and can be reproducibly detected, and they have the potential to be biomarkers for type 2 diabetes. We built a multi-parameter diagnostic model containing miR-148b, miR-223, miR-130a, and miR-19a. In the validation set, the area under curve of this model for the detection of type 2 diabetes was 0.90, and the sensitivity and specificity were 78.36% and 87.63%, respectively. This diagnostic model may be a novel tool for the detection of type 2 diabetes.